Transformation of point of interest geometries to lists of route segments in mobile communication device traffic analysis

ABSTRACT

A method to determine a traffic flow at a point-of-interest (POI). The method comprises determining route segments contained within a predefined POI geometry, creating a POI object that comprises the identities of the route segments contained within the POI geometry, whereby a geolocation of the POI is defined, for each of a plurality of mobile communication devices, determining route segments traversed by the mobile communication device based on geolocations of the device, and determining a number of different mobile communication devices that intersect with the POI based on comparing the route segments traversed by the mobile communication devices to the route segments associated to the POI object, whereby a traffic flow at the geolocation of the POI is determined.

CROSS-REFERENCE TO RELATED APPLICATIONS

None.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not applicable.

REFERENCE TO A MICROFICHE APPENDIX

Not applicable.

BACKGROUND

Geolocations of mobile communication devices can serve as proxies for geolocations of human beings. By determining the geolocation of mobile communication devices at specific times, storing this time-associated geolocation data in a data store, and analyzing the geolocation data, a variety of useful information can be generated. For example, a rate of human beings traversing an area at specific times of day and days of the week can be inferred. A speed of human beings (e.g., the cars which the human beings are driving or riding in) traversing an area can be inferred.

SUMMARY

In an embodiment, a geolocating method of converting a user defined point-of-interest (POI) geometry to a POI definition object comprising a collection of route segments, determining route segments traversed by a plurality of mobile communication devices based on geolocations of the devices, and analyzing the intersections of the route segments of the defined POIs and the route segments traversed by the mobile communication devices to determine a traffic flow at the geolocation of the POI is disclosed. The method comprises storing a map of travel routes in a first data store, where each travel route comprises a plurality of abutting route segments, presenting a user interface on a display screen by a point-of-interest (POI) definition application executing on a computer system, where the user interface shows at least some of the travel routes and receiving input by the POI definition application that defines a POI geometry as a location and one or more of a bearing, a radius, and a perimeter. The method further comprises determining by the POI definition application route segments contained within the POI geometry, creating a POI object by the POI definition application that comprises the identities of the route segments contained within the POI geometry, whereby a geolocation of the POI is defined, and storing the POI object by the POI definition application in a second data store. The method further comprises, for each of a plurality of mobile communication devices, determining route segments traversed by the mobile communication device based on geolocations of the device by an analysis application executing on a computer system, reading the POI object by the analysis application from the second data store and determining by the analysis application a number of different mobile communication devices that intersect with the POI based on comparing the route segments traversed by the mobile communication devices to the route segments associated with the POI object, whereby a traffic flow at the geolocation of the POI is determined.

In another embodiment, a geolocating system that converts a user defined point-of-interest (POI) geometry to a POI definition object comprising a collection of route segments, determines route segments traversed by a plurality of mobile communication devices based on geolocations of the devices, and analyzes the intersections of the route segments of the defined POIs and the route segments traversed by the mobile communication devices to determine a traffic flow at the geolocation of the POI is disclosed. The system comprises at least one processor, a non-transitory memory, a point-of-interest (POI) definition application stored in the non-transitory memory, and an analysis application stored in the non-transitory memory. When executed by the at least one processor, the POI definition application determines route segments contained within a predefined POI geometry, creates a POI object that comprises the identities of the route segments contained within the POI geometry, whereby a geolocation of the POI is defined, and stores the POI object in the data store. When executed by the at least one processor, the analysis application, for each of a plurality of mobile communication devices, determines route segments traversed by the mobile communication device based on geolocations of the device, reads the POI object from the data store, and determines a number of different mobile communication devices that intersect with the POI based on comparing the route segments traversed by the mobile communication devices to the route segments associated to the POI object, whereby a traffic flow at the geolocation of the POI is determined.

In yet another embodiment, a geolocating method of converting a user defined point-of-interest (POI) geometry to a POI definition object comprising a collection of route segments, determining route segments traversed by a plurality of mobile communication devices based on geolocations of the devices, and analyzing the intersections of the route segments of the defined POIs and the route segments traversed by the mobile communication devices to determine a traffic flow at the geolocation of the POI is disclosed. The method comprises determining by a POI definition application executing on a computer system route segments contained within a predefined POI geometry, creating a POI object by the POI definition application that comprises the identities of the route segments contained within the POI geometry, whereby a geolocation of the POI is defined, and storing the POI object by the POI definition application in a second data store. The method further comprises, for each of a plurality of mobile communication devices, determining route segments traversed by the mobile communication device based on geolocations of the device by an analysis application executing on a computer system, reading the POI object by the analysis application from the second data store, and determining by the analysis application a number of different mobile communication devices that intersect with the POI based on comparing the route segments traversed by the mobile communication devices to the route segments associated to the POI object, whereby a traffic flow at the geolocation of the POI is determined.

These and other features will be more clearly understood from the following detailed description taken in conjunction with the accompanying drawings and claims.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the present disclosure, reference is now made to the following brief description, taken in connection with the accompanying drawings and detailed description, wherein like reference numerals represent like parts.

FIG. 1 is a block diagram of a system according to an embodiment of the disclosure.

FIG. 2 is a block diagram of a point-of-interest geometry.

FIG. 3 is a block diagram of a point-of-interest definition object data structure according to an embodiment of the disclosure.

FIG. 4A and FIG. 4B are a flow chart of a method according to an embodiment of the disclosure.

FIG. 5 is a block diagram of a computer system according to an embodiment of the disclosure.

DETAILED DESCRIPTION

It should be understood at the outset that although illustrative implementations of one or more embodiments are illustrated below, the disclosed systems and methods may be implemented using any number of techniques, whether currently known or not yet in existence. The disclosure should in no way be limited to the illustrative implementations, drawings, and techniques illustrated below, but may be modified within the scope of the appended claims along with their full scope of equivalents.

Geolocation data pertaining to mobile communication devices can be collected by wireless communication service providers and analyzed to derive valuable information on the presence, dwell times, and movements of human beings. This information can be used to plan and adapt highway systems, construction plans, and business plans. This information can be used to establish values and prices for presenting content on billboards and on digital screens outside of the home. It is observed that in such analysis, the geolocation of the mobile communication device serves as a proxy for the geolocation of the human being using the mobile communication device.

The geolocation data associated with a single mobile communication device can be analyzed to determine a travel route that the user of the device traverses, for example when commuting from home to work and/or when commuting from work to home. This analysis may rely on one or more digital map of existing roads and may snap geolocation data to the nearest road. In an embodiment, the digital map may represent roads or routes as a sequence of route segments that abut one another. For example a first end of a first route segment abuts a first end of a second route segment, a second end of the second route segment abuts a first end of a third route segment, a second end of the third route segment abuts a first end of a fourth route segment, etc. In an embodiment, these route segments may comprise mathematical abstractions or computer representations referred to as edges and vertices (route segments abut one another at the vertices).

The route of the single mobile communication device can then be represented as a sequence of route segments. To determine if the device (and the associated human user) passes through or next to a point-of-interest (POI)—which may be referred to herein as an intersection of the device with the POI—a geography of the POI may be analyzed with reference to the sequence of route segments traversed by the device. This determination may be carried out by applications executing on computer systems daily for tens of millions of devices and for hundreds of thousands of different POIs.

A determination of intersections of devices with POIs on a national scale may consume about 6 hours of computing time in a given computer system, where the geolocations of the POIs are defined using customary geolocation coordinates, for example defined by latitude-longitude pairs. This kind of definition of geolocations of the POIs may further involve defining a geometry around the point of the latitude-longitude pairs that the POI encloses, for example from the consideration of what points a driver or rider in a vehicle may be able to observe and experience an advertisement presented on a large billboard beside a roadway. The POI geometry may comprise the geolocation, an orientation, and a perimeter. In an embodiment, the POI geometry may comprise a geolocation and a radius, where the perimeter of the POI geometry is understood to be a circle centered on the geolocation having the defined radius.

The present disclosure teaches a system and method of performing these intersection determinations based on first transforming a predefined POI geometry to a POI definition object that defines the POIs in terms of a collection of route segments and then analyzes intersections based on the collection of route segments associated with the POI definition object. By defining the POIs as a collection of route segments, the intersection algorithm can move away from geometrical and mathematical operations to simpler and quicker look-up and comparison operations. Said in other words, by defining POIs as a collection of route segments, intersection analysis can be transformed from processor intensive mathematics to simple database look-ups, for example a database join function call based on route segment identity. It is expected that using this approach can reduce the same determination of intersections of devices with POIs on a national scale on the same given computer system to 3 hours or less of computing time, achieving a significant time savings. This increased computing efficiency may save operating costs (e.g., cloud computing resources are often priced in part based on time measured consumption of resources), save electrical power, and also permit applications that are infeasible under slower computation cycles.

The system comprises a POI definition application that provides a user interface for use in defining POI geometries. The POI geometry can be defined by specifying a geolocation that is a point within the POI, for example a central point of the POI. The POI geometry can then specify a radius that defines the scope of the POI to include points that lie within a circle centered on the geolocation and having the specified radius. The geometry can specify a different shaped perimeter, and the POI is defined to include points that lie within the specified perimeter. The geometry can specify a bearing of the POI.

A map of travel routes comprising a plurality of route segments is stored in a data store. The POI definition application accesses the data store, reads at least some of the map information, and presents a map which can be zoomed into and zoomed out of by a user accessing the POI definition application on a laptop computer, for example via a web browser executing on the laptop computer. The presentation shows travel routes including the names of streets for reference by users. The user can provide input to the user interface to draw a perimeter around a location which he or she deems to be the area of the POI. The POI definition application uses the perimeter drawn around the POI to define a POI geometry. This POI geometry may be referred to as a predefined POI geometry.

In an embodiment, the data store may store a plurality of different maps, each map associated with a different travel mode. For example, the data store may store a first map associated with a highway travel mode, a second map associated with a light rail travel mode, a third map associated with an on-foot travel mode (e.g., a footpath travel mode), a fourth map associated with a subway travel mode, and a fifth map associated with a bus travel mode.

The POI definition application analyzes the POI geometry to determine what route segments lie wholly and/or partially within the geometry, for example within a perimeter defined by the POI geometry. The route segments that lie within or geometry may comprise route segments of any of the different type of travel modes. For example, the route segments may comprise highway travel mode route segments, light rail travel mode route segments, on-foot travel mode route segments, subway travel mode route segments, and/or bus travel mode route segments. The POI definition application creates a POI definition object that comprises one or more entries, each entry identifying one of the route segments selected by the user input. The entry may further identify a tile within which the route segment is located. A tile may be an area partition that provides computing efficiency gains by restricting intersection calculations to areas smaller than the entire United States, smaller than the entire state of Kansas, smaller than an entire county. In an example, a tile may define about a 5 square mile area. Tile sizes may vary depending on a density of POIs within the tiles and/or of population.

An analysis application may execute to analyze the geolocation data associated with a large number of mobile communication devices and determine route segments these devices traverse. This analysis can take account of the timestamps or time-date values included in geolocation data of the mobile communication devices. The analysis application may analyze the geolocation data of the devices daily or on some other periodic schedule. The analysis application may then compare the route segments traversed by a mobile communication device to one or more POI definition objects to see if any of the route segments included in a POI definition object matches a route segment traversed by the mobile communication device. When such a match occurs, an intersection is deemed to have occurred between the mobile communication device (and the associated human being) and the POI. The analysis application can count the total of all such intersections of devices with a POI and create totals per units of time (daily counts, hourly counts) and can determine rates of intersections over units of time.

Upon occasion, the POI geometry may be changed, for example because the environment of the POI changes. A building may be erected, changing the access to the POI, and militating a change to the POI geometry. A building may be demolished, changing access to the POI, and militating a change to the POI geometry. The user assessment of the area pertaining to the POI may change, militating a change to the POI geometry. In this case, the user can use the user interface to define the POI geometry again. The POI definition application can again generate the associated POI definition object representing the POI geometry in terms of route segments contained at least in part within a perimeter of the POI geometry.

In some cases, it may be desired to derive information about traffic associated with secondary locations that do not have a defined POI geometry. In an embodiment, the secondary location can be associated with one or more defined POI geometries. For example, the secondary location may be associated with an entry in a data store that associates the identity of the secondary location to one or more identities of defined POI geometries. These identities of defined POI geometries are deemed proximate to the secondary location—“close enough” to the secondary location—and counts of intersections of mobile devices with the POI geometry are ascribed to the secondary location. It is noted that, after initially creating the association of the secondary location identity to one or more identities of POI geometries, the processing described here is a simple quick database look up. This kind of proxying of intersection counts to secondary locations can provide significant efficiency in processing. In an embodiment, POI geometries are converted to a geohash values, and the POI geometries that are proximate to a given secondary location is determined by comparing the geohash values of the POI geometries and the geohash of the secondary location. In an embodiment, the search for POI geometries proximate to a given secondary location is restricted to one or more location geographical tiles proximate to the secondary location.

Defining POIs in terms of route segments enables calculating intersections of route segments traversed by a mobile communication device with those POIs defined as a delimited set of route segments, thereby providing considerable computing efficiency as contrasted with determining intersections of route segments with POIs defined as latitude-longitude pairs coupled with an enclosing perimeter. This increased processing efficiency may make it feasible to process historic device location data reaching back months for new partners (e.g., bringing on-board a new POI proprietor) to provide retrospective insight into traffic at their location. Further, this increased computing efficiency also enables the iterative tuning of POI definitions, because the recomputation—once the route traversed by a mobile communication device has been defined in terms of route segments—is a mere data store lookup versus the new definition of the POI in terms of route segments.

Turning now to FIG. 1, a system 100 is described. In an embodiment, the system 100 comprises a plurality of points-of-interest (POIs) 102, a first plurality of mobile communication devices (UEs) 104 a, a second plurality of UEs 104 b, and a third plurality of UEs 104 c. The POIs 102 may be associated with buildings, sports venues, billboards, or presentation screens. The first plurality of UEs 104 a may establish a wireless communication link to a first cell site 106 a that communicatively couples the UEs 104 a to a network 108. The second plurality of UEs 104 b may establish a wireless communication link to a second cell site 106 b that communicatively couples the UEs 104 b to the network 108. The third plurality of UEs 104 c may establish a wireless communication link to a third cell site 106 c that communicatively couples the UEs 104 c to the network 108. The UEs 104 may be any of a mobile phone, a smart phone, a personal digital assistant (PDA), a wearable computer, a headset computer, a laptop computer, a notebook computer, or a tablet computer. The network may be one or more private networks, one or more public networks, or a combination thereof.

Geolocation information associated with the UEs 104 may be collected and stored in a location data store 119. Some of the geolocation information may be provided by at least some of the UEs 104 through self-locating, for example using a GPS receiver on a UE 104 and sending GPS location coordinates to the location data store 119. Some of the geolocation information may be provided by the cell sites 106, for example providing the geolocation of a cell site 106 as a proxy for the geolocation of a UE 104 attached via a wireless link to the cell site 106. Some of the geolocation information may be provided by trilateration techniques, for example by analyzing signal strengths of a radio signal emitted by a UE 104 received by a plurality of cell sites 106 at known geolocations. The geolocation information associated with the UEs 104 may be referred to in some contexts as location fixes of the UEs 104. The geolocation information associated with a UE 104 may be deemed a proxy for geolocation information on a user of the UE 104, for example a wireless communication service subscriber. The geolocation information is stored in the location data store 119 as a geolocation along with an associated timestamp (date and time) identifying when the UE 104 was determined or inferred to be at the geolocation. In some contexts herein, when geolocation information is referred to, both the geolocation and an associated timestamp are referenced. In other contexts, for example when discussing definitions of POIs, when geolocation information is referred to, only a geolocation and not an associated timestamp is referenced. The geolocation may be identified with latitude-longitude values, with a geohash value, or with another location identity system.

This geolocation information associated with the UEs 104 may desirably be analyzed to determine proximity of the UEs 104 to the POIs 102. For example, analysis may be able to determine how many UEs 104 passed within eyesight of a POI 102 (e.g., a digital billboard). Analysis may be able to determine how long on average UEs 104 dwell in proximity to a POI 102 (e.g., a restaurant in an office building). This analysis can be summarized in statistics that are segmented by time slots, for example hourly time slots or half-hour time slots. The presence of a UE 104 proximate to a POI 102 may be referred to as an intersection of the UE 104 with the POI 102.

The system 100 further comprises one or more work stations 116 and an analysis server 118 that executes an analysis application 120 that analyzes the geolocation data associated with the UEs 102 (e.g., location fixes of the UEs 102) stored in the location data store 119. The work stations 116 and the analysis server 118 may be implemented as computer systems. Computer systems are described further hereinafter.

In embodiment, when the UE 104 is moving on a road or a light rail line there may be an insufficient number of location fixes in the location data store 119 to smoothly trace the travel route followed by the UE 104, for example from a residence to a work place. The analysis application 120 may access a digital map data store 110 to read one or more digital maps of existing roads, light rail tracks, footpaths, and/or other travel route types. The analysis application 120 may then infer a travel route taken by the UE 104 from a first geolocation to a second geolocation by imputing the unknown path taken by the UE 104 to be an algorithmically selected route in the digital map that connects the two geolocations. The first geolocation and the second geolocation may each separately be determined by the analysis application 120 as a centroid of a plurality of geolocations that are located close to each other. For example, when a user is at work during a workday, a plurality of geolocations may be captured and stored in the location data store 119, where the geolocations are located close to each other (e.g., within 200 feet of each other).

For example, when a user is at home after work, a plurality of geolocations may be captured and stored in the location data store 119, where the geolocations are located close to each other. In some contexts, the plurality of geolocations located close to each other (e.g., within a predefined radius of the centroid, for example a radius of 300 feet or a radius of 1000 feet) may be referred to as a cluster of location fixes or as simply a cluster. The first geolocation may be defined by the geolocation of the centroid of a first cluster of location fixes of a UE 104 and the second geolocation may be defined by the geolocation of the centroid of a second cluster of location fixes of the same UE 104. The timestamp associated with the first geolocation may be a latest timestamp of the location fixes associated with the first cluster, and the timestamp associated with the second geolocation may be the earliest timestamp of the location fixes associated with the second cluster. Alternatively, the timestamp associated with the first geolocation may be an earliest timestamp of the location fixes associated with the first cluster, and the timestamp associated with the second geolocation may be the latest timestamp of the location fixes associated with the second cluster.

This imputed route may be algorithmically selected based at least in part on identifying a shortest path between actual geolocation data points or location fixes (or cluster centroids), for example using an open source routing machine. Imputing the route comprises imputing the actual geolocations to a route, even though the actual geolocation may not be located on a route. This may be referred to in some contexts as snapping the geolocation to a route. The geolocation may not actually be on a route because the geolocation location information is imprecise (e.g., the UE 104 was on a route, but the location information has a 50 yard error which places it off the route) or because the UE 104 was not on a route (e.g., the UE 104 was in an NFL stadium not physically on a roadway).

Based on the actual geolocations and the time stamps associated with the actual geolocations for the UE 104 (or the centroid and timestamp of a cluster of geolocations of the UE 104), inferred geolocations of the UE 104 between the two actual geolocations and along the imputed route can be determined and associated to a time stamp by the analysis application 120 and an inferred rate of travel between the two actual geolocations can be determined. These inferred geolocations can be stored in the location data store 119 and used along with actual geolocations by the analysis application 120. This process of determining inferred geolocations can be performed for any number of UEs 104. In an embodiment, the process of determining inferred geolocations for UEs 104 may be performed daily. For more details on location clusters and inferring geolocations and/or location fixes of the UE 104, see U.S. patent application Ser. No. 15/944,512 filed Apr. 3, 2018, titled “Mobile Viewshed Analysis,” by Prashanth Dannamaneni, et al, which is incorporated herein by reference in its entirety.

In an embodiment, the digital maps stored in the digital map data store 110 may represent roads or routes as a sequence of route segments that abut one another. For example a first end of a first route segment abuts a first end of a second route segment, a second end of the second route segment abuts a first end of a third route segment, a second end of the third route segment abuts a first end of a fourth route segment, etc. In an embodiment, these route segments may comprise mathematical abstractions or computer representations referred to as edges and vertices (route segments abut one another at the vertices). A route traversed by a UE 104 can then be represented as a sequence of route segments. To determine if the device (and the associated human user) passes through or next to a point-of-interest (POI)—which may be referred to herein as an intersection of the device with the POI—the analysis application 120 can analyze a definition of the POI with reference to the sequence of route segments traversed by the device.

Turning now to FIG. 2, an illustration of a POI geometry 125 defining a POI 102 is described. While a POI 102 (e.g., a point-of-interest) may be referred to as a point, in fact the POI 102 is commonly extended in two dimensions and possibly three dimensions. The extended region associated with a POI 102 may be partially related to the inherent indefiniteness of geolocations associated with UEs 104. The extended region associated with a POI 102 may be related to the human response due to proximity to a location. For example, if one is running weekend errands which involve driving within 200 feet of a specialty coffee shop, this may be close enough that one treats oneself to a cup of specialty coffee, whereas if one drives only within 1000 feet of the same specialty coffee shop, one does not bother to interrupt the smooth completion of errands by making that detour. With reference to a billboard, a POI 102 may be the extended area from which the billboard can be viewed and taken in (e.g., text content read, visual image comprehended). This extended area associated with a POI 102 may be modeled as the area enclosed by a perimeter 128. Additionally, the POI 102 may be associated with a bearing or orientation 127, for example a direction from which the POI 102 can most effectively be experienced. The POI 102 may also be represented by a point location 126, much as an extended city may be represented abstractly by a single point such as a city hall or a county court house when calculating distances between different cities by mapping software.

A POI geometry 125 (e.g., a data structure stored in a data store) can be defined corresponding to the POI 102. In an embodiment, the POI geometry 125 comprises the location 126, the orientation 127, and the perimeter 128. The location 126 can be articulated in the format of latitude-longitude coordinates, in the format of a geohash, or in another location description format. The orientation 127 can be articulated in an angular degree unit format, an angular radians unit format, or another angle measure format. The perimeter 128 can be articulated in any desired format, for example an ordered sequence of locations that define vertices of a polygon that forms the perimeter 128. The POI geometry 125 may further comprise a POI identity 130 and an optional time window duration 132.

With reference now to both FIG. 1 and FIG. 2, the system 100 further comprises a server 112 and a POI definition application 114. The server 112 may be implemented as a computer system. In an embodiment, the POI definition application 114 and the analysis application 120 may execute on the same computer system. The POI definition application 114 provides a user interface (UI) that may be presented on a display of a work station 116 for use in defining a POI geometry 125 and thereby defining an associated POI 102. In an embodiment, the UI may be a web page presented in a browser executing on the work station 116, and the POI definition application 114 may be implemented as a web application. The UI may present a plurality of travel routes representing streets, railway lines, footpaths, and/or sidewalks along with identifying names. The UI may promote a user drawing a closed figure on the display to represent the perimeter of a POI 102, for example to represent a region or area from which a billboard may be visible. In some contexts the user drawing the closed figure on the display, for example using a mouse or other computer input device, may be referred to as providing a drawing input to the work station 116 and or to the user interface of the POI definition application 114. This drawing input (e.g., POI perimeter demarcation) may be transmitted from the workstation 116 to the POI definition application 114 via the network 108. The UI may further promote the user drawing the orientation 127 and specifying the location 126. The POI definition application 114 may translate these user inputs to create and provide values to the POI geometry 125 and then store the POI geometry 125 in a POI definition data store 122. In an embodiment, the user may input a value of the time window duration 132 of the POI geometry 125 for use in avoiding multiple counts of intersections of location fixes with the POI 102 within the time window duration, as described more fully below. The POI identity 130 may be assigned by the POI definition application 114 and/or by the user.

The POI definition application 114 also analyzes the POI geometry 125 to automatically generate a POI definition articulated as a plurality of route segments contained at least partially within the perimeter 128 of the POI geometry 125. For example, the POI definition application determines which of the route segments in the digital map read from the digital map data store 110 are at least partially contained within the perimeter 128 and adds those route segments to a POI definition object. The determination of intersections of UEs 104 with POIs 102 described above may be carried out by the analysis application 120 daily for tens of millions of different UEs 104 and for hundreds of thousands of different POIs 102. This intersection analysis can be performed much more efficiently by a computer system when it is performed as a series of database look-ups—database joins on route segments associated with actual and inferred geolocations of UEs 104 and route segments associated to POIs 102—than when it is performed by performing the more complex mathematical operations used to determine intersections of route segments with POI geometry 125.

Turning now to FIG. 3, a block diagram of a POI definition object 140 is described. In an embodiment, the POI definition object 140 comprises a plurality of route segment entries 142. Each route segment entry 142 comprises a route segment identity 144. The route segment entry 142 may optionally further comprise a tile identity 146. In an embodiment, the POI definition object 140 may comprise a POI identity 148 and a time window duration 150.

In an embodiment, the analysis of intersection of geolocations of UEs 104 with POIs 102 may be performed based on partitioning a large region (e.g., the United States) into a plurality of geographic tiles. Geographic tiles may be defined as regions of 100 square miles or less, regions of 25 square miles or less, regions of 10 square miles or less, or regions of 5 square miles or less. The analysis application 120 may determine what geographic tiles the POI 102 is contained within, based on the geographic tiles the route segment identities 144 of the POI definition object 140 are associated with. The analysis application 120 may then access geolocation data of one or more UE 104 from the location data store 119 selecting those geolocation data entries that are associated with one of the geographic tiles associated with the POI 102. The analysis application 120 then analyzes this restricted population of geolocation data entries for possible intersections with the route segments of the POI definition object 140, whereby the computational magnitude of the analysis is constrained and made more efficient.

An intersection of a geolocation—either an actual geolocation or an inferred geolocation—is deemed to occur when a geolocation of the UE 104 is located on the same route segment as one of the route segment entries 142 of the POI definition object 140. In calculating counts of intersections of UEs 104 with the POI 102, the analysis application 120 may exclude all but one intersection of a given UE 104 with the same POI 102, for example within a predefined time window. Thus, three intersections of a UE 104 with a POI 102 within 20 seconds would be deemed a single intersection which lasted about 20 seconds. Other predefined time windows may be used in determining counts of intersections of UEs 104 with a POI 102. In an embodiment, the POI geometry 125 may have a time window duration 132 parameter whose value may be defined by a user via the user interface of the POI definition application 114, and the value of the time window duration 132 may be stored in the time window duration 150 parameter of the POI definition object 140 for use in excluding duplicate intersections from an intersection count.

With reference now to FIGS. 1, 2, and 3, the process of the using the user interface of the POI definition application 114 may be referred to in some contexts as curating the POI definition. Curation of the POI definition can include causing the analysis application 120 to analyze UE 104 intersections with the POI 102, to derive statistics on those intersections, and to present the statistics in the display of the UI of the work station 116. After reviewing the statistics presented in the UI, the user may use the UI to adapt the POI definition by redrawing the perimeter 128 of the POI 102 on the display of travel routes. This process may be repeated as often as desired to curate the POI definition. In an embodiment, the user may successively adapt the POI definition to cause the results of intersection analysis (e.g., counts of intersections and/or statistics related to intersections) to converge with authoritative metrics obtained from some source, such as government traffic statistics.

In an embodiment, the UI and the POI definition application 114 may allow the user of the work station 116 to initially define the POI 102 by drawing a highway travel route mode perimeter, a light rail travel route mode perimeter, and a footpath travel route mode perimeter. The digital maps would distinguish between route segments that are associated with a highway travel mode, route segments that are associated with a light rail travel mode, and route segments that are associated with a foot path travel mode. Alternatively, different digital maps may be provided for different travel modes. The POI definition application 114 would create a highway travel mode POI geometry 125, a light rail travel mode POI geometry 125, and a footpath travel mode POI geometry 125. The POI definition application 114 would then analyze each of the highway mode POI geometry 125, the light rail mode POI geometry 125, and the footpath mode POI geometry 125 to generate the POI definition object 140. Alternatively, the POI geometry 125 may comprise one or more route segment entries 142 identified as highway travel mode entries, one or more route segment entries 142 identified as light rail travel mode entries, and one or more route segment entries 142 identified as footpath travel mode entries. Thus, the POI definition object 140 may comprise route segment entries 142 that are associated with route segments in a highway mode digital map, route segment entries 142 that are associated with route segments in a light rail mode digital map, and route segment entries 142 that are associated with route segments in a footpath mode digital map. Alternatively, the POI geometry 125 may comprise one or more route segment entries 142, one or more route segment entries 142, and one or more route segment entries 142, without distinguishing among the route segment entries 142 based on travel mode types. An intersection of a geolocation of a UE 104 with the POI 102 would then be determined if a geolocation of the UE 104 coincided with any one of a highway mode route entry 142, a light rail mode route entry 142, or a footpath mode route entry 142 of the POI definition object 140 associated with the subject POI 102.

Turning now to FIG. 4A and FIG. 4B, a method 200 is described. In an embodiment, the method 200 is a geolocating method of converting a user defined point-of-interest (POI) geometry to a POI definition object comprising a collection of route segments, determining route segments traversed by a plurality of mobile communication devices based on geolocations of the devices, and analyzing the intersections of the route segments of the POI definition object and the route segments traversed by the mobile communication devices to determine a traffic flow at the POI. The traffic flow may be determined as a count of intersections of UEs 104 with a POI 102, for example a number of intersections of UEs 104 with a POI 102 per unit of time. The results of analysis by the analysis application 120, for example counts of intersections and/or statistics about counts of intersections, may be stored in a results data store 124.

At block 202, the method 200 comprises storing a map of travel routes in a first data store, where each travel route comprises a plurality of abutting route segments. In an embodiment, these route segments may comprise mathematical abstractions or computer representations referred to as edges and vertices (route segments abut one another at the vertices). In an embodiment, the processing of block 202 may comprise storing a plurality of maps in the first data store, for example storing a plurality of digital maps in the map data store 110. Each of the plurality of digital maps may cover a different sub-region of a larger region. For example, the digital maps may comprise a plurality of state digital maps that collectively compose a digital map of the United States. For example, the digital maps may comprise an east coast digital map, a mid-west digital map, a southern digital map, a mountain region digital map, a southwest coast digital map, and a northwest digital map that collectively compose a digital map of the United States. Alternatively, or in addition, the different digital maps may represent travel routes associated with different travel types, for example one or more highway travel mode digital maps, one or more light rail travel mode digital maps, and one or more footpath travel mode digital maps.

At block 204, the method 200 comprises presenting a user interface on a display screen by a point-of-interest (POI) definition application executing on a computer system, where the user interface shows at least some of the travel routes. The user interface may provide functionality for a user to identify a state, a city, or a town as a center of the display and to zoom into the map (to make features bigger to cover less territory) and to zoom out of the map (to make features smaller to cover more territory). The travel routes may be presented in different formats to distinguish highway route travel mode portions from light rail route travel mode portions from foot path travel mode portions.

At block 206, the method 200 comprises receiving input by the POI definition application that defines a POI geometry as a location and one or more of a bearing, a radius, and/or a perimeter. The perimeter may be defined by a user drawing in a user interface of the POI definition application, for example using a mouse or other input device. In an embodiment, the processing of block 206 may comprise the user entering a perimeter for each of a highway travel mode POI geometry, a light rail travel mode POI geometry, and a footpath travel mode POI geometry. In an embodiment, the processing of block 206 may comprise receiving input by the POI definition application that defines a value of the time window duration 132 of the POI geometry 125.

At block 208, the method 200 comprises determining by the POI definition application route segments contained within or at least partially within the POI geometry. In an embodiment the processing of block 208 comprises determining route segments contained at least partially within the highway travel mode POI geometry, route segments contained at least partially within the light rail travel mode POI geometry, and route segments contained at least partially within the footpath travel mode POI geometry.

At block 210, the method 200 comprises creating a POI object by the POI definition application that comprises the identities of the route segments contained within or at least partially within the POI geometry, whereby a geolocation of the POI is defined. In some contexts, the POI object is referred to as a POI definition object. In an embodiment, the processing of block 210 comprises creating a POI object for each of route segments associated with the highway travel mode, route segments associated with the light rail travel mode, and route segments associated with the footpath travel mode. In an embodiment, the processing of block 210 comprises copying the value of a time window duration from the POI geometry to the POI object. At block 212, the method 200 comprises storing the POI object by the POI definition application in a second data store.

At block 214, the method 200 comprises, for each of a plurality of mobile communication devices, determining route segments traversed by the mobile communication device based on geolocations of the device by an analysis application executing on a computer system. The processing of block 214 comprises reading geolocation data from the location data store 119. The geolocation data may comprise actual geolocation data as well as inferred geolocation data (e.g., actual location fixes and inferred location fixes). The geolocation data read from the location data store 119 may be selected based on a tile or plurality of tiles that are associated with the route segments identified in the POI object.

At block 216, the method 200 comprises reading the POI object by the analysis application from the second data store. At block 218, the method 200 comprises determining by the analysis application a number of different mobile communication devices that intersect with the POI based on comparing the route segments traversed by the mobile communication devices to the route segments associated with the POI object, whereby a traffic flow at the geolocation of the POI is determined. The processing of block 218 comprises comparing the route segments traversed by the mobile communication devices to the route segments associated with the POI object. When a match occurs, this match is deemed a candidate intersection. The processing of block 218 may further analyze a plurality of intersections of the same mobile communication device with the POI that occur within a predefined window of time and deem these to be a single intersection rather than a plurality of intersections.

It is noted that the processing of block 202 may be repeated rarely, for example when routes in a digital map are changed. The processing of blocks 204 through 212 may be repeated as often as the POI 102 is deemed to have changed for any reason. The processing of block 214 through 218 may be repeated periodically, for example daily and or weekly.

FIG. 5 illustrates a computer system 380 suitable for implementing one or more embodiments disclosed herein. The computer system 380 includes a processor 382 (which may be referred to as a central processor unit or CPU) that is in communication with memory devices including secondary storage 384, read only memory (ROM) 386, random access memory (RAM) 388, input/output (I/O) devices 390, and network connectivity devices 392. The processor 382 may be implemented as one or more CPU chips.

It is understood that by programming and/or loading executable instructions onto the computer system 380, at least one of the CPU 382, the RAM 388, and the ROM 386 are changed, transforming the computer system 380 in part into a particular machine or apparatus having the novel functionality taught by the present disclosure. It is fundamental to the electrical engineering and software engineering arts that functionality that can be implemented by loading executable software into a computer can be converted to a hardware implementation by well-known design rules. Decisions between implementing a concept in software versus hardware typically hinge on considerations of stability of the design and numbers of units to be produced rather than any issues involved in translating from the software domain to the hardware domain. Generally, a design that is still subject to frequent change may be preferred to be implemented in software, because re-spinning a hardware implementation is more expensive than re-spinning a software design. Generally, a design that is stable that will be produced in large volume may be preferred to be implemented in hardware, for example in an application specific integrated circuit (ASIC), because for large production runs the hardware implementation may be less expensive than the software implementation. Often a design may be developed and tested in a software form and later transformed, by well-known design rules, to an equivalent hardware implementation in an application specific integrated circuit that hardwires the instructions of the software. In the same manner as a machine controlled by a new ASIC is a particular machine or apparatus, likewise a computer that has been programmed and/or loaded with executable instructions may be viewed as a particular machine or apparatus.

Additionally, after the system 380 is turned on or booted, the CPU 382 may execute a computer program or application. For example, the CPU 382 may execute software or firmware stored in the ROM 386 or stored in the RAM 388. In some cases, on boot and/or when the application is initiated, the CPU 382 may copy the application or portions of the application from the secondary storage 384 to the RAM 388 or to memory space within the CPU 382 itself, and the CPU 382 may then execute instructions that the application is comprised of. In some cases, the CPU 382 may copy the application or portions of the application from memory accessed via the network connectivity devices 392 or via the I/O devices 390 to the RAM 388 or to memory space within the CPU 382, and the CPU 382 may then execute instructions that the application is comprised of. During execution, an application may load instructions into the CPU 382, for example load some of the instructions of the application into a cache of the CPU 382. In some contexts, an application that is executed may be said to configure the CPU 382 to do something, e.g., to configure the CPU 382 to perform the function or functions promoted by the subject application. When the CPU 382 is configured in this way by the application, the CPU 382 becomes a specific purpose computer or a specific purpose machine.

The secondary storage 384 is typically comprised of one or more disk drives or tape drives and is used for non-volatile storage of data and as an over-flow data storage device if RAM 388 is not large enough to hold all working data. Secondary storage 384 may be used to store programs which are loaded into RAM 388 when such programs are selected for execution. The ROM 386 is used to store instructions and perhaps data which are read during program execution. ROM 386 is a non-volatile memory device which typically has a small memory capacity relative to the larger memory capacity of secondary storage 384. The RAM 388 is used to store volatile data and perhaps to store instructions. Access to both ROM 386 and RAM 388 is typically faster than to secondary storage 384. The secondary storage 384, the RAM 388, and/or the ROM 386 may be referred to in some contexts as computer readable storage media and/or non-transitory computer readable media.

I/O devices 390 may include printers, video monitors, liquid crystal displays (LCDs), touch screen displays, keyboards, keypads, switches, dials, mice, track balls, voice recognizers, card readers, paper tape readers, or other well-known input devices.

The network connectivity devices 392 may take the form of modems, modem banks, Ethernet cards, universal serial bus (USB) interface cards, serial interfaces, token ring cards, fiber distributed data interface (FDDI) cards, wireless local area network (WLAN) cards, radio transceiver cards that promote radio communications using protocols such as code division multiple access (CDMA), global system for mobile communications (GSM), long-term evolution (LTE), worldwide interoperability for microwave access (WiMAX), near field communications (NFC), radio frequency identity (RFID), and/or other air interface protocol radio transceiver cards, and other well-known network devices. These network connectivity devices 392 may enable the processor 382 to communicate with the Internet or one or more intranets. With such a network connection, it is contemplated that the processor 382 might receive information from the network, or might output information to the network in the course of performing the above-described method steps. Such information, which is often represented as a sequence of instructions to be executed using processor 382, may be received from and outputted to the network, for example, in the form of a computer data signal embodied in a carrier wave.

Such information, which may include data or instructions to be executed using processor 382 for example, may be received from and outputted to the network, for example, in the form of a computer data baseband signal or signal embodied in a carrier wave. The baseband signal or signal embedded in the carrier wave, or other types of signals currently used or hereafter developed, may be generated according to several methods well-known to one skilled in the art. The baseband signal and/or signal embedded in the carrier wave may be referred to in some contexts as a transitory signal.

The processor 382 executes instructions, codes, computer programs, scripts which it accesses from hard disk, floppy disk, optical disk (these various disk based systems may all be considered secondary storage 384), flash drive, ROM 386, RAM 388, or the network connectivity devices 392. While only one processor 382 is shown, multiple processors may be present. Thus, while instructions may be discussed as executed by a processor, the instructions may be executed simultaneously, serially, or otherwise executed by one or multiple processors. Instructions, codes, computer programs, scripts, and/or data that may be accessed from the secondary storage 384, for example, hard drives, floppy disks, optical disks, and/or other device, the ROM 386, and/or the RAM 388 may be referred to in some contexts as non-transitory instructions and/or non-transitory information.

In an embodiment, the computer system 380 may comprise two or more computers in communication with each other that collaborate to perform a task. For example, but not by way of limitation, an application may be partitioned in such a way as to permit concurrent and/or parallel processing of the instructions of the application. Alternatively, the data processed by the application may be partitioned in such a way as to permit concurrent and/or parallel processing of different portions of a data set by the two or more computers. In an embodiment, virtualization software may be employed by the computer system 380 to provide the functionality of a number of servers that is not directly bound to the number of computers in the computer system 380. For example, virtualization software may provide twenty virtual servers on four physical computers. In an embodiment, the functionality disclosed above may be provided by executing the application and/or applications in a cloud computing environment. Cloud computing may comprise providing computing services via a network connection using dynamically scalable computing resources. Cloud computing may be supported, at least in part, by virtualization software. A cloud computing environment may be established by an enterprise and/or may be hired on an as-needed basis from a third party provider. Some cloud computing environments may comprise cloud computing resources owned and operated by the enterprise as well as cloud computing resources hired and/or leased from a third party provider.

In an embodiment, some or all of the functionality disclosed above may be provided as a computer program product. The computer program product may comprise one or more computer readable storage medium having computer usable program code embodied therein to implement the functionality disclosed above. The computer program product may comprise data structures, executable instructions, and other computer usable program code. The computer program product may be embodied in removable computer storage media and/or non-removable computer storage media. The removable computer readable storage medium may comprise, without limitation, a paper tape, a magnetic tape, magnetic disk, an optical disk, a solid state memory chip, for example analog magnetic tape, compact disk read only memory (CD-ROM) disks, floppy disks, jump drives, digital cards, multimedia cards, and others. The computer program product may be suitable for loading, by the computer system 380, at least portions of the contents of the computer program product to the secondary storage 384, to the ROM 386, to the RAM 388, and/or to other non-volatile memory and volatile memory of the computer system 380. The processor 382 may process the executable instructions and/or data structures in part by directly accessing the computer program product, for example by reading from a CD-ROM disk inserted into a disk drive peripheral of the computer system 380. Alternatively, the processor 382 may process the executable instructions and/or data structures by remotely accessing the computer program product, for example by downloading the executable instructions and/or data structures from a remote server through the network connectivity devices 392. The computer program product may comprise instructions that promote the loading and/or copying of data, data structures, files, and/or executable instructions to the secondary storage 384, to the ROM 386, to the RAM 388, and/or to other non-volatile memory and volatile memory of the computer system 380.

In some contexts, the secondary storage 384, the ROM 386, and the RAM 388 may be referred to as a non-transitory computer readable medium or a computer readable storage media. A dynamic RAM embodiment of the RAM 388, likewise, may be referred to as a non-transitory computer readable medium in that while the dynamic RAM receives electrical power and is operated in accordance with its design, for example during a period of time during which the computer system 380 is turned on and operational, the dynamic RAM stores information that is written to it. Similarly, the processor 382 may comprise an internal RAM, an internal ROM, a cache memory, and/or other internal non-transitory storage blocks, sections, or components that may be referred to in some contexts as non-transitory computer readable media or computer readable storage media.

While several embodiments have been provided in the present disclosure, it should be understood that the disclosed systems and methods may be embodied in many other specific forms without departing from the spirit or scope of the present disclosure. The present examples are to be considered as illustrative and not restrictive, and the intention is not to be limited to the details given herein. For example, the various elements or components may be combined or integrated in another system or certain features may be omitted or not implemented.

Also, techniques, systems, subsystems, and methods described and illustrated in the various embodiments as discrete or separate may be combined or integrated with other systems, modules, techniques, or methods without departing from the scope of the present disclosure. Other items shown or discussed as directly coupled or communicating with each other may be indirectly coupled or communicating through some interface, device, or intermediate component, whether electrically, mechanically, or otherwise. Other examples of changes, substitutions, and alterations are ascertainable by one skilled in the art and could be made without departing from the spirit and scope disclosed herein. 

What is claimed is:
 1. A geolocating method of converting a user defined point-of-interest (POI) geometry to a POI definition object comprising a collection of route segments, determining route segments traversed by a plurality of mobile communication devices based on geolocations of the mobile communication devices, and analyzing the intersections of the route segments of the POI definition object and the route segments traversed by the mobile communication devices to determine a traffic flow at the POI, comprising: storing a map of travel routes in a first data store, where each travel route comprises a plurality of abutting route segments; presenting a user interface on a display screen by a point-of-interest (POI) definition application executing on a computer system, where the user interface shows at least some of the travel routes; receiving an input by the POI definition application that defines a POI geometry as a location and one or more of a bearing, a radius, and a perimeter; determining by the POI definition application route segments contained within the POI geometry; creating a POI object by the POI definition application that comprises the identities of the route segments contained within the POI geometry, whereby a geolocation of the POI is defined; storing the POI object by the POI definition application in a second data store; for each of a plurality of mobile communication devices, determining route segments traversed by the mobile communication device based on geolocations of the device by an analysis application executing on a computer system; reading the POI object by the analysis application from the second data store; and determining by the analysis application a number of different mobile communication devices that intersect with the POI based on comparing the route segments traversed by the mobile communication devices to the route segments associated with the POI object, whereby a traffic flow at the geolocation of the POI is determined.
 2. The geolocating method of claim 1, wherein the route segments each comprise an edge terminated at each end by a vertex.
 3. The geolocating method of claim 1, wherein the POI is one of a billboard, a building, or a presentation screen.
 4. The geolocating method of claim 1, wherein the travel routes comprise highway routes, light rail routes, and foot path routes.
 5. The geolocating method of claim 4, wherein the input received by the POI definition application that defines a POI geometry defines a highway route POI geometry for at least one highway travel route of the map, a light rail route POI geometry for at least one light rail travel route of the map, and a footpath route POI geometry for at least one footpath travel route of the map and wherein determining route segments contained within the POI geometry comprises determining highway route segments contained at least partially within the highway route POI geometry, light rail route segments contained at least partially within the light rail route POI geometry, and determining footpath route segments contained at least partially within the footpath route POI geometry.
 6. The geolocating method of claim 1, wherein the geolocations are represented as geohashes or as latitude-longitude coordinates.
 7. The geolocating method of claim 1, wherein the mobile communication devices are selected from the group consisting of mobile phones, smart phones, headset computers, wearable computers, laptop computers, notebook computers, and tablet computers.
 8. The geolocating method of claim 1, wherein the route segments are associated with tiles and determining a number of different mobile communication devices that intersect with the POI is further based on the tiles of the route segments traversed by the mobile communication devices and the tiles of the route segments associated with the POI object.
 9. A geolocating system that converts a user defined point-of-interest (POI) geometry to a POI definition object comprising a collection of route segments, determines route segments traversed by a plurality of mobile communication devices based on geolocations of the mobile communication devices, and analyzes the intersections of the route segments of the POI definition object and the route segments traversed by the mobile communication devices to determine a traffic flow at the geolocation of the POI, comprising: at least one processor; a non-transitory memory; a data store comprising a map of travel routes, where each travel route comprises a plurality of abutting route segments; a point-of-interest (POI) definition application stored in the non-transitory memory that, when executed by the at least one processor: determines route segments contained within a predefined POI geometry, creates a POI object that comprises the identities of the route segments contained within the POI geometry, whereby a geolocation of the POI is defined, and stores the POI object in the data store; and an analysis application stored in the non-transitory memory that, when executed by the at least one processor: for each of a plurality of mobile communication devices, determines route segments traversed by the mobile communication device based on geolocations of the device, reads the POI object from the data store, and determines a number of different mobile communication devices that intersect with the POI based on comparing the route segments traversed by the mobile communication devices to the route segments associated to the POI object, whereby a traffic flow at the geolocation of the POI is determined.
 10. The geolocating system of claim 9, wherein the travel routes comprise highway routes, light rail routes, and foot path routes.
 11. The geolocating system of claim 10, wherein the map comprises a first digital map comprising highway routes, a second digital map comprising light rail routes, and a third digital map comprising footpath routes.
 12. The geolocating system of claim 11, wherein the first digital map, the second digital map, and the third digital map represent route segments as an edge terminated at each end by a vertex.
 13. The geolocating system of claim 9, wherein the analysis application is executed periodically.
 14. The geolocating system of claim 13, wherein the analysis application is executed daily.
 15. The geolocating system of claim 9, wherein the geolocations are represented as geohashes or as latitude-longitude coordinates.
 16. A geolocating method of converting a user defined point-of-interest (POI) geometry to a POI definition object comprising a collection of route segments, determining route segments traversed by a plurality of mobile communication devices based on geolocations of the mobile communication devices, and analyzing the intersections of the route segments of the POI definition object and the route segments traversed by the mobile communication devices to determine a traffic flow at the POI, comprising: storing a map of travel routes in a first data store, where each travel route comprises a plurality of abutting route segments; determining by a point-of-interest (POI) definition application executing on a computer system route segments contained within a POI geometry; creating a POI object by the POI definition application that comprises the identities of the route segments contained within the POI geometry, whereby a geolocation of the POI is defined; storing the POI object by the POI definition application in a second data store; for each of a plurality of mobile communication devices, determining route segments traversed by the mobile communication device based on geolocations of the device by an analysis application executing on a computer system; reading the POI object by the analysis application from the second data store; and determining by the analysis application a number of different mobile communication devices that intersect with the POI based on comparing the route segments traversed by the mobile communication devices to the route segments associated with the POI object, whereby a traffic flow at the geolocation of the POI is determined.
 17. The geolocating method of claim 16, further comprising receiving an input by the POI definition application that defines the POI geometry, wherein some of the input is a drawing input defining a perimeter of the POI geometry.
 18. The geolocating method of claim 16, wherein the geolocations of mobile communication devices are each associated with a timestamp and wherein determining a number of different mobile communication devices that intersect with the POI comprises counting as one count multiple intersections of one mobile communication device that occur within a predefined period of time.
 19. The geolocating method of claim 18, wherein the POI geometry comprises the predefined period of time.
 20. The geolocating method of claim 15, wherein the geolocations are represented as geohashes or as latitude-longitude coordinates. 